Self-supervised learning based on discriminative nonlinear features for image classification

Volume: 38, Issue: 6, Pages: 903 - 917
Published: Jun 1, 2005
Abstract
For learning-based tasks such as image classification, the feature dimension is usually very high. The learning is afflicted by the curse of dimensionality as the search space grows exponentially with the dimension. Discriminant-EM (DEM) proposed a framework by applying self-supervised learning in a discriminating subspace. This paper extends the linear DEM to a nonlinear kernel algorithm, Kernel DEM (KDEM), and evaluates KDEM extensively on...
Paper Details
Title
Self-supervised learning based on discriminative nonlinear features for image classification
Published Date
Jun 1, 2005
Volume
38
Issue
6
Pages
903 - 917
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